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Predicting User Acceptance of Strong AI using Extension of Theory of Planned Behavior: Focused on the Age Group of 20s

확장된 계획적 행동이론을 통해 본 강한 인공지능 제품에 대한 이용자의 수용의도: 20대 연령층을 중심으로

  • 이창섭 (세종대학교 경영학부 부교수) ;
  • 이현정 (중앙대학교 융합교양학부 조교수)
  • Received : 2020.07.16
  • Accepted : 2020.10.06
  • Published : 2020.10.28

Abstract

The rapid progress of AI technology gives us the expectation to solutions to various problems in our society, and at the same time, it gives us anxiety about the side effects that can occur if AI develops beyond human control. This study was conducted in the early 20s with less objection to advanced devices. We attempted to provide clues to understand thoughts and attitudes of the targets about the future environment that will be brought by AI through the process of finding intent the acceptance of strong AI technology. For this, we applied the Theory of Planned Behavior, and further expanded this research model to identify factors affecting the attitude toward AI. As a result, the attitude toward AI and perceived behavioral control had a significant effect on the intention to use to strong AI. In addition, we found that the expectation of the benefit of improving task performance and the anxiety on the threat of relationship disturbance had a significant effect on the attitude toward AI. This study suggests implications for AI-related companies establishing the direction of technology development and for government setting a policy direction for AI adoption.

AI 기술의 급격한 진보는 우리 사회의 다양한 문제점을 개선해주는 기대를 주는 동시에, 인간이 제어할 수 없을 만큼 발전했을 경우 일어날 수 있는 다양한 부작용에 대한 불안을 안겨준다. 본 연구는 첨단 기기에 대한 거부감이 적은 20대 초반 젊은 층을 대상으로 강한 AI 기술이 적용된 제품의 수용의도를 알아보는 과정을 통해 AI에 의해 도래할 미래 환경에 대한 이들의 생각과 태도를 이해하는 단서를 제시하고자 하였다. 이를 위해 계획적 행동이론을 적용하였고, 나아가 이 연구모델을 확장시켜 AI에 대한 태도에 영향을 미치는 요인들을 확인해보고자 하였다. 연구 결과, AI 제품 사용의도에 AI에 대한 태도 및 지각된 행동통제가 유의한 영향을 미쳤고, AI에 대한 태도에는 업무 성과 향상의 혜택에 대한 기대와 관계 교란의 위협에 대한 불안의 영향을 확인하였다. 본 연구는 AI관련 기업 관점에서는 기술개발의 방향을 세우고, 국가적 관점에서는 AI의 정책적 수용 방향성을 세우는 데 시사점을 제시하며 연구적 공헌점을 가진다.

Keywords

References

  1. 박재원, 고재연, "손정의 '한국 집중할 건 첫째도 둘째도 AI'," 한국경제 2019.07.04. 기사, https://www.hankyung.com/politics/article/2019070422351
  2. 대한민국정책브리핑, "AI 국가전략 발표... 2030년 455조 창출.AI반도체 세계 1위, 과기정통부, 기재부, 교육부, 법무부, 문체부, 행안부, 2019.12.17. http://www.korea.kr/news/policyNewsView.do?newsId=148867621
  3. D. Santos, D. Giese, S. Brodehl, S. Chon, W. Staab, R. Kleinert, D. Maintz, and B. Baessler, "Medical students' attitude towards artificial intelligence: a multicentre survey," European Radiology, Vol.29, pp.1640-1646, 2019. https://doi.org/10.1007/s00330-018-5601-1
  4. 한해진, "의료 인공지능(AI) 성장 비약적, 암 정복 도전" 데일리메디, 2020.0204. 기사, http://www.dailymedi.com/detail.php?number=852457&thread=22r06
  5. M. Hengstler, E. Enkel, and S. Duelli, "Applied artificial intelligence and trust-The case of autonomous vehicles and medical assistance devices," Technological Forecasting & Social Change, Vol.105, pp.105-120, 2016. https://doi.org/10.1016/j.techfore.2015.12.014
  6. S. Popenici and S. Kerr, "Exploring the impact of artificial intelligence on teaching and learning in higher education," Research and Practice in Technology Enhanced Learning, Vol.12, No.22, 2017.
  7. 윤영주, "에어비앤비, AI로 잠재적인 위험 숙박객 막을 수 있다," AI타임즈, 2020.01.09. 기사, http://www.aitimes.com/news/articleView.html?idxno=124565
  8. 이재구, "우버, 뉴로팟 오픈소싱... 멀티 딥러닝 프레임워크 환경 통합," AI타임즈, 2020.06.09. 기사. http://www.aitimes.com/news/articleView.html?idxno=129262
  9. 김진석, "'약한' 인공지능과 '강한' 인공지능의 구별의 문제," 철학연구, 제117집, pp.111-137, 2017.
  10. R. Kurzwei, The singularity is near: When humans transcend biology, Penguin, 2005.
  11. C. Rory, "Stephen Hawking warns artificial intelligence could end mankind," BBC NEWS, 2014.12.02. https://www.bbc.com/news/technology-30290540
  12. B. Ryan, "Elon Musk warns A.I. could create an 'immortal director from which we can never escape'," CNBC, 2018.04.06. https://www.cnbc.com/2018/04/06/elon-musk-warns-ai-could-create-immortal-dictator-indocumentary.html
  13. I. Ajzen, "The theory of planned behavior," in Action control: from cognition to behavior, pp.11-30, 1991
  14. R. East, "Investment decisions and the theory of planned behavior," Journal of Economic Psychology, Vol.14, pp.337-375, 1993. https://doi.org/10.1016/0167-4870(93)90006-7
  15. M. Fishbein, "An investigation of the relationships between beliefs about and object and the attitude toward that object," Human relations, Vol.16, No.3, pp.233-239, 1963. https://doi.org/10.1177/001872676301600302
  16. F. Bass and W. Talarzyk, "An Attitude Model for the Study of Brand Preference," Journal of Marketing Research, Vol.9, No.1, pp.93-96, 1972. https://doi.org/10.1177/002224377200900121
  17. D. Lehmann, "Television show preference: application of a choice model," Journal of Marketing Research, Vol.8, No.1, pp.47-55, 1971. https://doi.org/10.1177/002224377100800106
  18. J. Ginter, "An experimental investigation of attitude change and choice of a new brand," Journal of Marketing Research, Vol.11, No.1, pp.30-40, 1974. https://doi.org/10.1177/002224377401100103
  19. M. Fishbein and I. Ajzen, Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, MA, 1975.
  20. S. Taylor and P. Todd, "Assessing IT usage: the role of prior experience," MIS Quarterly, Vol.19, No.4, pp.561-570, 1995. https://doi.org/10.2307/249633
  21. V. Venkatesh and F. Davis, "A theoretical extension of the technology acceptance model: four longitudinal field studies," Management Science, Vol.46, No.2, pp.186-204, 2000. https://doi.org/10.1287/mnsc.46.2.186.11926
  22. J. Schepers and M. Wetzels, "A meta-analysis of the technology acceptance model: investigating subjective norm and moderation effects," Information & Management, Vol.44, No.1, pp.90-103, 2007. https://doi.org/10.1016/j.im.2006.10.007
  23. I. Ajzen, "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Vol.50, No.2, pp.179-211, 1991. https://doi.org/10.1016/0749-5978(91)90020-T
  24. T. Madden, P. Ellen, and I. Ajzen, "A comparison of the theory of planned behavior and the theory of reasoned action," Personality and Social Psychology Bulletin, Vol.18, No.1, pp.3-9, 1992. https://doi.org/10.1177/0146167292181001
  25. P. Sparks and R. Shepherd, "Self-identity and the theory of planned behavior: assessing the role of identification with green consumerism," Social Psychology Quarterly, Vol.55, No.4, pp.388-399, 1992. https://doi.org/10.2307/2786955
  26. P. Zhang and S. Aikman, "Attitudes in ICT acceptance and use," International conference on human-computer interaction, pp.1021-1030, Springer, 2007.
  27. K. Yang, "Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior," Journal of Retailing and Consumer Service, Vol.19, No.5, pp.484-491, 2012 https://doi.org/10.1016/j.jretconser.2012.06.003
  28. H. Yang, H. Lee, and H. Zo, "User acceptance of smart home services: an extension of the theory of planned behavior," Industrial Management & Data Systems, Vol.117, No.1, pp.68-89, 2017. https://doi.org/10.1108/IMDS-01-2016-0017
  29. 이창섭, 이현정, "인공지능 혁신에 대한 기대와 불안요인 및 영향 연구," 한국콘텐츠학회논문지, Vol.19, No.9, pp.37-46, 2019. https://doi.org/10.5392/jkca.2019.19.09.037
  30. T. Luor, H, Lu, H. Cheng, and C. Hsu, "Exploring the critical quality attributes and models of smart homes," Maturitas, Vol.82, No.4, pp.277-386, 2015.
  31. L. Ulrich, "Substitute or Synthesis? The Interplay between Human and Artificial Intelligence," Research-Technology Management, Vol.61, No.5, pp.12-14, 2018.
  32. R. Likert, "A Technique for the Measurement of Attitudes,"Archives of Psychology, Vol.140, pp.1-55, 1932.
  33. E. Erdfelder, F. Faul and A. Buchner, "GPOWER: A general power analysis program. Behavior research methods," instruments, & computers, Vol.28, No.1, pp.1-11, 1996. https://doi.org/10.3758/BF03203630
  34. C. Ringle, S. Wende, S. and S. Will, SmartPLS 2.0 (M3) Beta, Hamburg, 2005.
  35. 신건권, 석박사힉위 및 학술논문 작성 중심의 SmartPLS 3.0 구조방정식모델링, 청람, 2018.